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Data Platform Engineer – IntermediateKey Highlights??? Build and expand core data platform components powering analytics, experimentation, and algorithm development? Develop scalable ETL, streaming, and metadata systems using Spark, Kafka, and modern lakehouse technologies?? Support high-volume data transformation, federated querying, and performance optimization?? Strengthen RBAC, data governance, and secure access patterns for multi-team data environments?? Enable experimentation and data development with reliable tooling and automated data workflowsPosition OverviewWe are seeking anIntermediate Data Platform Engineerto help build and scale a modern data ecosystem.In this role, you'll contribute to distributed data systems, ETL/streaming pipelines, metadata platforms, and frameworks that support experimentation across the organization.You will develop platform features, enhance observability, ensure data reliability, and collaborate with engineering and data science teams to support new initiatives.Key ResponsibilitiesData Platform EngineeringBuild and maintain scalable data storage, transformation, and processing systemsSupport Iceberg-based data lakehouse architecture and metadata catalogsDevelop ETL and streaming pipelines using Spark, Kafka, Parquet, and IcebergBuild backend services in Python, Go, Scala, or Java to enhance platform capabilitiesContribute to Trino query performance and metadata optimizationExperimentation & Analytics EnablementDevelop tooling that improves experiment design, tracking, and analysisCollaborate with data science and analytics teams to support experimentation workflowsAutomate components of A/B testing and experimentation frameworksData Reliability, Security & GovernanceMaintain and improve platform-level RBAC and AWS IAM configurationUse Datadog for logging, alerting, and monitoring platform performanceSupport schema evolution, data quality, and reproducibility across pipelinesInfrastructure & DeploymentDeploy and support services using Kubernetes and HelmImprove automation, performance, and cost efficiency of data workloadsContribute to capacity planning for data-intensive servicesCollaboration & DocumentationParticipate in cross-team engineering discussionsDocument platform components to support internal stakeholdersQualificationsDegree in Computer Science, Engineering, or related field3+ yearsin data platform, data engineering, or platform engineeringProduction-level coding experience inPython,Go,Scala, orJavaExperience supportingIceberg-based data warehousesHands-on experience withSpark,Kafka,Trino, and distributed systemsFamiliarity with RBAC systems, IAM, and data governance principlesExperience with Kubernetes, Helm, and CI/CD workflowsStrong troubleshooting and communication skillsWhy Join UsJoin a team focused on building scalable, modern data infrastructure that powers experimentation and analytics.You'll gain exposure to leading-edge tools and architectures while contributing to systems used across the organization.
